Can a marketer drive the stock price of the firm? Yes, it should be possible. Toward this endeavor, the authors develop a framework to link customer equity (CE) (as determined by the customer lifetime value metric) to market capitalization (MC) (as determined by the stock price of the firm). The authors test the framework in an empirical field experiment with two Fortune 1000 firms in the business-to-business and business-to-consumer contexts, respectively. The findings show that (1) a CE-based framework can reliably predict the MC of the firm and (2) marketing strategies directed at increasing the CE not only increase the stock price of the firm but also beat market expectations. Furthermore, the results indicate that the relationship between CE and MC is moderated by risk factors in the form of volatility and vulnerability of cash flows from customers. By accounting for these factors, the authors improve the association between CE and MC. The findings broaden the scope and role of marketing while reinforcing the importance of the marketer to any organization.

The firm-customer exchange process consists of three key parts: (1) firm-initiated marketing communications, (2) customer buying behavior, and (3) customer product return behavior.To date, the literature in marketing has largely focused on how marketing communications affect customer buying behavior and, to some extent, how past buying behavior affects a firm's decisions to initiate future marketing communications. However, the literature on product returns is sparse, especially in relation to analyzing individual customer product return behavior. Although the magnitude of the value of product returns is known to be high ($100 billion per year), how it affects customer buying behavior is not known because of a lack of data availability and understanding of the role of product returns in the firm-customer exchange process. Given that product returns are considered a hassle for a firm's supply chain management and a drain on overall profitability, it is important to study product return behavior. Thus, the authors empirically demonstrate the role of product returns in the exchange process by determining the exchange process factors that help explain product return behavior and the consequences of product returns on future customer and firm behavior. In addition, the authors demonstrate that product returns are inevitable but by no means evil.

Through field experiments conducted in two business-to-business firms, the authors evaluate the financial and relational consequences of adopting a customer focus in sales campaigns. In both the experiments, salespeople adopting the customer-focused sales campaign coordinated their sales calls with the objective of selling all the products that a customer was predicted to purchase only at the time the customer was expected to purchase. The authors compare this strategy with the current practice in the organization in which salespeople for each product category independently contacted the customers who were expected to purchase in that category without any guidance on the expected timing of customer purchase. The experiments show that adopting a customer-focused sales campaign can significantly increase firm profits and return on investment. The total incremental profits obtained from implementing the customer-focused sales campaign was more than $1 million. High-revenue customers were the source of improvements in the efficiency of marketing contacts, whereas low-revenue customers were the source of improvements in the effectiveness of the marketing contacts. A customer-focused sales campaign also improved the relationship quality between the customer and the firm. This research provides empirical evidence for theoretical expectations of the benefits provided by a customer-focused sales campaign. Organizations can use the field experiments illustrated in this study as a template for implementing the first step in migrating to a customer-centric organization.

Marketing managers are being required to demonstrate the profitability of their marketing actions down to the level of their individual customers and on an ongoing basis. At the same time, customers expect firms to increasingly customize their products and services to meet their demands. Firms still need to produce superior products, sell smarter, and understand the markets as a whole, but the ability of firms to orient themselves to interact successfully with their individual customers will differentiate them in the future. Advances in technology have resulted in increasing opportunities for interactions between firms and customers, between customers, and between firms. An interaction orientation reflects a firm's ability to interact with its individual customers and to take advantage of information obtained from them through successive interactions to achieve profitable customer relationships. First, the authors identify the components of interaction orientation: (1) customer concept, (2) interaction response capacity, (3) customer empowerment, and (4) customer value management. Second, they relate interaction orientation to both customer-level and aggregate-level performance measures. Third, they identify the antecedents of interaction orientation. Fourth, they examine the moderating effects of customer-initiated contacts and competitive intensity on the interaction orientation-performance linkage. The results are based on a survey of top marketing managers. The commonly held view that customer-based relational performance is related to customerbased profit performance is not supported. However, both customer-based relational performance and customerbased profit performance affect aggregate business-level performance positively. Interaction orientation is a phenomenon observed in both business-to-business and business-to-consumer firms. The extent of customerinitiated contacts moderates the interaction orientation–performance relationship.

The authors explore the drivers of multichannel shopping and the impact of multichannel shopping on customer profitability. Through a longitudinal analysis, the authors provide evidence that multichannel shopping is associated with higher customer profitability. Using the social exchange theory, they develop hypotheses regarding the impact of several customer-firm interaction characteristics on customer channel adoption duration. They propose a shared-frailty hazard model for testing the proposed hypotheses. They use the customer database of an apparel manufacturer that sells through three distinct channels for the empirical analysis and find that frequency-related interaction characteristics have the greatest influence on second-channel adoption duration. In contrast, proportion of returns, a purchase-related interaction characteristic, has the greatest influence on third-channel adoption duration. Variation across customers in purchase-related attributes has a greater impact on the duration to adopt the second channel than the duration to adopt the third channel. In contrast, variation across customers in the channel-related attributes has a greater impact on the third-channel adoption duration than on the second-channel adoption duration. The customer-firm interaction characteristics identified in this study and the proposed model framework allow for forward-looking allocation of multichannel marketing resources.

In this research, the authors present a modeling framework for balancing resources between customer acquisition efforts and customer retention efforts. The key question that the framework addresses is, “What is the customer profitability maximizing balance?” In addition, they answer questions about how much marketing spending to allocate to customer acquisition and retention and how to distribute those allocations across communication channels.

The authors evaluate the usefulness of customer lifetime value (CLV) as a metric for customer selection and marketing resource allocation by developing a dynamic framework that enables managers to maintain or improve customer relationships proactively through marketing contacts across various channels and to maximize CLV simultaneously. The authors show that marketing contacts across various channels influence CLV nonlinearly. Customers who are selected on the basis of their lifetime value provide higher profits in future periods than do customers selected on the basis of several other customer-based metrics. The analyses suggest that there is potential for improved profits when managers design resource allocation rules that maximize CLV. Managers can use the author’s framework to allocate marketing resources efficiently across customers and channels of communication.

For too long, marketers have not been held accountable for showing how marketing expenditures add to shareholder value. As time has gone by, this lack of accountability has undermined marketers’ credibility, threatened the standing of the marketing function within the firm, and even threatened marketing’s existence as a distinct capability within the firm. This article proposes a broad framework for assessing marketing productivity, cataloging what is already known, and suggesting areas for further research. The authors conclude that it is possible to show how marketing expenditures add to shareholder value. The effective dissemination of new methods of assessing marketing productivity to the business community will be a major step toward raising marketing’s vitality in the firm and, more important, toward raising the performance of the firm itself. The authors also suggest many areas in which further research is essential to making methods of evaluating marketing productivity increasingly valid, reliable, and practical.

The authors develop a framework that incorporates projected profitability of customer in the computation of lifetime duration. Furthermore, the authors identify factors under a manager's control that explain the variation in the profitable lifetime duration. They also compare other frameworks with the traditional methods such as the recency, frequency, and monetary value and illustrate the superiority of the proposed framework. Finally, the authors develop several key implications that can be of value to decision makers in managing customer relationships.

Relationship marketing emphasizes the need for maintaining long-term customer relationships. It is beneficial, in genera, to serve customers over a longer time, especially in a contractual relationship. However, it is not clear whether some of the findings observed in a contractual setting hold good in noncontractual scenarios: relationships between a seller and a buyer that are no governed by a contract or membership. The authors offer four different propositions in this study and subsequently test each one in a noncontractual context. The four propositions relate to whether (1) there exists a strong positive customer-lifetime-probability relationship, (2) profits increase over time, (3) the costs of serving long-life customers are no less, and (4) long-life customer pay higher prices. The authors develop arguments both for and against each of the propositions. The data for this study, obtained from a large catalog retailer, cover a three-year window and are recorded on a daily basis. The empirical findings observed in this study challenge all the expectations derived from the literature. Long-life customers are not necessarily profitable customers. The authors develop plausible explanations for findings that go against the available evidence in the literature and identify three indicators through discriminant analysis that can help manager focus their efforts on more profitable customers. The authors draw several marketing implications and acknowledge the limitations of the study.

The authors focus on their 1990 model (B&K; see Balasubramanian and Kumar 1990), which indicates that market share, market growth, and their interaction are important predictors of the ratio of advertising and promotional costs to sales (A&P/S). In sharp contrast, Ailawadi, Farris, and Parry's (1994; AFP) subsequent replication attempt asserts that market share and market growth are not good predictors of A&P/S. The authors' research documents serious problems in AFP's study, including erroneous model estimates caused by incorrect execution of the SAS TSCSREG procedure, pooling data for analysis in ways that cannot be justified statistically, data preparation errors, and inappropriate operationalizations of market share and market growth. With regard to analyses of Profit Impact of Market Strategy and brand-level data reported by AFP, the authors again find that AFP have analyzed data in inappropriate ways, given the conceptual framework of the B&K model. Because these problems provide compelling evidence to disregard AFP's results, the authors conclude that the criticisms advanced by AFP against the B&K model are not valid.

The authors extend prior research on explaining variations in the intensity of marketing communication (i.e., advertising and promotional expenditures/sales) with a simple model estimated on cross-sectional time-series data. Analysis on firm-level data pooled at the industry level, performed for each of several industries belonging to different markets, attest to the model’s explanatory power. Model validation analyses show an impressive similarity of model parameters and goodness of fit across split-half data samples for each industry analyzed. Further, for all industries belonging to a given market, the results indicate remarkable consistency in the signs of the associations between marketing communication intensity and (1) market share, (2) market growth, and (3) their interaction. However, this consistency does not hold across all markets. Plausible explanations for these results are advanced.